Abstract

The problem of collecting, analysing and evaluating evidence on adverse drug reactions is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of health care practice. Philosophical discussions have analysed critically the methodological pitfalls and epistemological implications of evidence assessment in medicine; however, they have focused predominantly on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special focus on the privileged role assigned to randomized controlled trials (RCTs) in evidence-based medicine. Regardless of whether the RCT's privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference in relation to intended and unintended effects, in that the unknowns at stake are heterogeneous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their primary focus is methodological and regards the fact that bias and confounding factors do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood as being different in evidence for risk versus for efficacy. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. The upshot of my analysis is that different epistemologies confer different methodological choices, which in turn bring about relevant practical implications such as the decision to restrict or suspend drug use rather than leaving it on the market. Thus, it is worth considering the criteria underlying our evidence constraints because they may be ill suited to the purpose for which they are used.